---
license: cc-by-nc-4.0
task_categories:
- image-feature-extraction
language:
- en
tags:
- medical
- image
- biometry
- biometrics
- measurement
- x-ray
- cephalogram
- head
- neck
pretty_name: ceph-biometrics-400
size_categories:
- n<1K
---


![HF-Ceph-Biometrics-400](HF-Ceph-Biometrics-400.png)


## About
This is a modified version of [data](https://figshare.com/s/37ec464af8e81ae6ebbf) for the paper: 
[Fully Automatic System for Accurate Localisation and Analysis of Cephalometric Landmarks in Lateral Cephalograms](https://doi.org/10.1038/srep33581)

**Dataset Summary:**
- 400 head and neck X-ray scans and 19 landmarks for each image

**What's new?**
- We saved the original 2D `.bmp` images into pseudo 3D `.nii.gz` files in a manner that the original
  2D sagittal slices can be extracted from the 3D NIfTI files correctly assuming the standard RAS+
  orientation of `.nii.gz` files. A pseudo voxel size [0.1, 0.1, 0.1] is set in the NIfTI header,
  according to the data description in the paper: "The image resolution was 1935 × 2400 pixels with
  a pixel spacing of 0.1 mm."
- We used the landmark annotations from the folder `400_senior` in the original dataset.
- We changed the landmarks coordinates to 3D, making it consistent with the new 3D NIfTI files.
- Figures of image and landmarks are added for visual inspection.
- Images (`.nii.gz` files), landmarks (`.json` files) and figures (`.png` files) are saved in
  `Images`, `Landmarks`, and `Landmarks-fig` folders.


## Changelog 🔥
- [8 May, 2025] Update the JSON files in `Landmarks.zip` to use **0-based** slice indices. ‼️
- [6 Mar, 2025] Update landmark coordinates to **0-based indices**. ‼️
- [3 Mar, 2025] Update the data structure of JSON files within `Landmarks.zip`. Landmarks coordinates remain unchanged.
- [1 Mar, 2025]
  - Update `Landmarks.zip`: correct the coordinates in JSON files. It's recommended to redownload all compressed files.
  - Add a data preparation script `get_dataset.py`.
  - Add data usage agreement.


## Data Usage Agreement
By using the dataset, you agree to the terms as follow.
- You must cite the paper: [Fully Automatic System for Accurate Localisation and Analysis of Cephalometric Landmarks in Lateral Cephalograms](https://doi.org/10.1038/srep33581)
- You must refer to the source of this dataset in any publication:
  `https://huggingface.co/datasets/YongchengYAO/Ceph-Biometrics-400`


## Download from Huggingface
```bash
#!/bin/bash
pip install --upgrade huggingface-hub[cli]
huggingface-cli login --token $HF_TOKEN
```
```python
# python
from huggingface_hub import snapshot_download
snapshot_download(repo_id="YongchengYAO/Ceph-Biometrics-400", repo_type='dataset', local_dir="/your/local/folder")
```


## Landmarks Labels
```python
landmarks_map = {
    "P1": "sella",
    "P2": "nasion",
    "P3": "orbitale",
    "P4": "porion",
    "P5": "subspinale",
    "P6": "supramentale",
    "P7": "pogonion",
    "P8": "menton",
    "P9": "gnathion",
    "P10": "gonion",
    "P11": "incision inferius",
    "P12": "incision superius",
    "P13": "upper lip",
    "P14": "lower lip",
    "P15": "subnasale",
    "P16": "soft tissue pogonion",
    "P17": "posterior nasal spine",
    "P18": "anterior nasal spine",
    "P19": "articulare",
}
```


# From Raw Data
You can replicate the data processing step by running the script:
```bash
python get_dataset.py -d <datasets_folder> -n Ceph-Biometrics-400
```


## License
This dataset is released under the `CC BY-NC 4.0` license.